Advances in computational logistics and supply chain analytics

Contributor(s):

Material type: Text

TextSeries: Unsupervised and Semi-Supervised LearningPublication details: Springer Cham 2024Description: xiv, 196 pISBN:

9783031500350

Subject(s):

Supply chain analytics

DDC classification:

658.7 ALH

Summary: This book provides advances in computational logistics and supply chain analytics. The authors include innovative data-driven and learning-based approaches, methods, algorithms, techniques, and tools that have been designed or applied to create and implement a successful logistics and supply chain management process. This book highlights the state of the art and challenges related to the design and the application of computational methods to solve logistic and supply chain management problems. The authors present recent computational logistic methods and supply chain analytics techniques designed and applied to support managers in improving such complex processes. This book broadly covers recent computational methods and techniques applied to ensure continuous improvement of transport, logistic, and supply chain management processes. Readers can rapidly explore these new methods and their applications to solve such complex problems. (https://link.springer.com/book/10.1007/978-3-031-50036-7)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	658.7 ALH (Browse shelf(Opens below))	1	Available		007896

Table of contents:
Front Matter
Pages i-xiv
Download chapter PDF
The Dynamic Vehicle Routing Problem: A Comprehensive Survey
Nasreddine Ouertani, Hajer Ben-Romdhane, Saoussen Krichen
Pages 1-36
Multi-Objective Optimization for Electric Vehicle Routing Problem: Literature Review
Anouar Haddad, Takwa Tlili, Saoussen Krichen
Pages 37-58
A Decision Support System for Solving the Windy Rural Postman Problem
Takwa Tlili, Marwa Harzi, Saoussen Krichen
Pages 59-73
A Hybrid Meta-Heuristic to Solve Flexible Job Shop Scheduling Problem
Makram Zaidi, Amina Amirat, Bassem Jarboui, Abdelkrim Yahyaoui
Pages 75-98
Multimodal Freight Transport Optimization Based on Economic and Ecological Constraint
Lilia Rejeb, Abir Chaabani, Hajer Safi, Lamjed Ben said
Pages 99-127
Solving Hierarchical Production–Distribution Problem Based on MDVRP Under Flexibility Depot Resources in Supply Chain Management
Abir Chaabani, Lamjed Ben Said
Pages 129-147
Analysis of Inhibitors to Implementing Digital Supply Chain in Saudi Arabia: An Interpretive Structural Modeling (ISM) Approach
Raouf Jaziri, Abdullah Alshareef, Saleh Alnahdi, Mohammad Miralam
Pages 149-172
Financial Performance Measurement of Logistics Companies: Empirical Evidence from Saudi Arabia
Raéf Bahrini, Ahmed Zamzam, Assaf Filfilan
Pages 173-194
Back Matter
Pages 195-196

(https://link.springer.com/book/10.1007/978-3-031-50036-7)

This book provides advances in computational logistics and supply chain analytics. The authors include innovative data-driven and learning-based approaches, methods, algorithms, techniques, and tools that have been designed or applied to create and implement a successful logistics and supply chain management process. This book highlights the state of the art and challenges related to the design and the application of computational methods to solve logistic and supply chain management problems. The authors present recent computational logistic methods and supply chain analytics techniques designed and applied to support managers in improving such complex processes. This book broadly covers recent computational methods and techniques applied to ensure continuous improvement of transport, logistic, and supply chain management processes. Readers can rapidly explore these new methods and their applications to solve such complex problems.

(https://link.springer.com/book/10.1007/978-3-031-50036-7)

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